Because excessive torque on a machine component may lead to failure of the component, it is often desired to know, during operation of a machine, how much torque is being applied to one or more locations on the machine and whether such torque is excessive. For example, a machine having a drivetrain, e.g., an engine, torque converter, transmission, driveshaft, differential, and axle shafts, generates and/or transmits torque all along the drivetrain during operation. The torque at these locations provides the power to perform the specific work functions demanded, but also creates stresses on the components, thereby impacting the life of the various portions of the drivetrain. Therefore, it is desired to have a torque estimator that can estimate the torque applied to various drivetrain components in real time as the machine operates and provide an indication if excessive torque is being applied to the drivetrain component for which torque is being estimated.
One method of estimating torque at various locations on a machine is described in U.S. Pat. No. 6,757,604 (the '604 patent) issued to Carlson et al. on Jun. 29, 2004. The '604 patent describes a method and apparatus for determining a value of torque at a desired location on a machine. The method of the '604 patent includes choosing the desired location, determining an operating condition relevant to the desired location, determining a plurality of parameters of the machine, and determining a torque value at the desired location as a function of the operating conditions and plurality of parameters. Various neural networks and equations are used to determine torque value.
Although the system of the '604 patent may estimate torque at various locations on a machine using a neural network or equation, it may not be applicable to determining imminent component failure in real time onboard a machine. In particular, because the system of the '604 patent may use neural networks and equations to merely determine torque, it may be inapplicable to detecting imminent component failure in real time onboard a machine using a data structure, such as, for example, a histogram that may represent a duration of time the machine spent operating at specific combinations of estimated torque and another drivetrain component parameter.
The system of the '604 patent may estimate torque at various locations on a machine using a relatively complex arrangement of input conditions, parameters, neural networks and equations. The system of the '604 patent, however, may be unable to estimate torque values, such as, for example, torque converter output torque and differential pinion torque using a more limited number of engine or drivetrain parameters. Processing a more limited number of parameters may be desirable for reasons related to improving performance of a torque estimating module by reducing computing cycles, data bus traffic, or the like.
Although the arrangement of neural networks and equations in the system of the '604 patent may estimate torque at various locations on a machine, the system may not be applicable to automatic configuration on various machines based on machine type. For example, the method of the '604 may not include an ability to select appropriate neural networks or equations based on a variable that identifies a machine type on which the torque estimator may be operating.
The disclosed system and method are directed to overcoming one or more of the problems set forth above.